Methods, systems, and media for detecting spoofing in mobile authentication

ABSTRACT

Provided herein are devices, systems, and methods for detecting spoofing of a 3D object, using a 2D representation, in a mobile object authentication process, comprising capturing image data of the 3D object by a front-facing camera, to record a current spatial characteristic of the 3D object, while a front-facing screen displays an authentication pattern comprising a plurality of regions, wherein at least one of the regions varies in at least one of: brightness, position, size, shape, and color over time causing a variance of lighting effects which create highlights and shadows on the 3D object over time. The devices, systems, and methods thereby provide an efficient and secure process for determining if spoofing of the 3D object, using a 2D representation, is attempted in a mobile authentication process, by comparing the current spatial characteristic of the 3D object with a stored reference spatial characteristic of the 3D object.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. application Ser. No.16/134,781, filed on Sep. 18, 2018, which claims the benefit of U.S.Provisional Application No. 62/560,038, filed Sep. 18, 2017, which ishereby incorporated by reference in its entirety.

BACKGROUND

“Spoofing” a security system is generally defined as an act ofmasquerading as an authenticated user, by submitting false data. In thiscase, methods of liveness detection may be employed to determine whethera biometric modality, such as a face, a palm (palm print), a finger(fingerprint), or an ear, carries the unique structural qualities of theoriginal three-dimensional biometric modality, or is-a two-dimensionalreplicate.

SUMMARY

Many current technologies for optical recognition of identity can beeasily spoofed or hacked. In the case of facial recognition on mobiledevices, for example, it is common for the facial recognition algorithmsto be tricked into accepting a fake representation of a user's face, aspresented via an image of the user's face on the front-facing videoscreen of another mobile device, or as presented via a print-out of theuser's face on paper, among other methods of identity spoofing.Moreover, biometric implementations such as the facial recognitionalgorithm described in this example, providing identity management onmobile devices, are a regular feature of mobile devices across theworld, and there is a current unmet need for an automated authenticationtechnology for optical recognition of identity, while maintainingimmunity to spoofing attempts.

One aspect disclosed herein is a mobile device comprising: afront-facing camera, a front-facing screen, at least one processor, amemory, an operating system configured to perform executableinstructions, and a computer program including instructions executableby the at least one processor to run an application for detectingspoofing of a 3D object, using a 2D representation, in a mobile objectauthentication process, the application comprising: a software modulecapturing, via the front-facing camera, image data of the 3D objectwhile displaying, via the front-facing screen, an authentication patterncomprising a plurality of regions, wherein at least one of the regionsvaries in at least one of: brightness, position, size, shape, and colorover time causing a variance of lighting effects which create highlightsand shadows on the 3D object over time; a software module using theimage data and the authentication pattern to determine a current spatialcharacteristic of the 3D object; and a software module determining ifspoofing of the 3D object, using a 2D representation, is attempted inthe mobile authentication process by comparing the current spatialcharacteristic of the 3D object with a stored reference spatialcharacteristic of the 3D object.

In some embodiments, the 3D object comprises a face, a palm (palmprint), a finger (fingerprint), or an ear. In some embodiments, the 2Drepresentation comprises a photograph of the 3D object. In someembodiments, the image data comprises a plurality of photographs of the3D object. In some embodiments, the image data comprises a video of the3D object. In some embodiments, the authentication pattern comprises aplurality of images. In some embodiments, the authentication patterncomprises a video. In some embodiments, the plurality of regions arearranged in two or more vertical or horizontal bands in theauthentication pattern. In some embodiments, the plurality of regionsare arranged in a horizontal band across the top or bottom of thescreen, or in a vertical band across the left or right side of thescreen in the authentication pattern. In some embodiments, theauthentication pattern comprises variation of at least one region in atleast one of: brightness, position, size, shape, and color to form aregular pulse or a random pulse in the authentication pattern. In someembodiments, at least one of the regions varies in position over time toform a translation or rotation of the region in the authenticationpattern. In some embodiments, at least one of the regions varies in sizeover time to form a contraction or expansion of the region in theauthentication pattern. In some embodiments, the application furthercomprises a software module receiving a request to authenticate the 3Dobject. In some embodiments, the application further comprises asoftware module instructing a user to orient the front-facing camera ofthe mobile device in a fixed position relative to the object during thecapturing of the image data. In some embodiments, the variation of atleast one region in at least one of: brightness, position, size, shape,and color encode information in the authentication pattern.

A second aspect disclosed herein is a system for detecting spoofing of a3D object, using a 2D representation, in a mobile object authenticationprocess, the system comprising: a mobile device comprising afront-facing camera, a front-facing screen, at least one processor, amemory; and a server comprising at least one processor and a memory: themobile device configured to: capture, via the front-facing camera, imagedata of the 3D object while displaying, via the front-facing screen, anauthentication pattern comprising a plurality of regions, wherein atleast one of the regions varies in at least one of: brightness,position, size, shape, and color over time causing a variance oflighting effects which create highlights and shadows on the 3D objectover time; and transmit the image data and the authentication pattern tothe server; the server configured to: receive the image data and theauthentication pattern from the mobile device; use the image data andthe authentication pattern to determine a current spatial characteristicof the 3D object; determine if spoofing of the 3D object, using a 2Drepresentation, is attempted in the mobile authentication process bycomparing the current spatial characteristic of the 3D object with astored reference spatial characteristic of the 3D object; and transmit aresult spoofing result to the mobile device.

In some embodiments, the 3D object comprises a face, a palm (palmprint), a finger (fingerprint), or an ear. In some embodiments, the 2Drepresentation comprises a photograph of the 3D object. In someembodiments, the image data comprises a plurality of photographs of the3D object. In some embodiments, the image data comprises a video of the3D object. In some embodiments, the authentication pattern comprises aplurality of images. In some embodiments, the authentication patterncomprises a video. In some embodiments, the plurality of regions arearranged in two or more vertical or horizontal bands in theauthentication pattern. In some embodiments, the plurality of regionsare arranged in a horizontal band across the top or bottom of thescreen, or in a vertical band across the left or right side of thescreen in the authentication pattern. In some embodiments, theauthentication pattern comprises variation of at least one region in atleast one of: brightness, position, size, shape, and color to form aregular pulse or a random pulse in the authentication pattern. In someembodiments, at least one of the regions varies in position over time toform a translation or rotation of the region in the authenticationpattern. In some embodiments, at least one of the regions varies in sizeover time to form a contraction or expansion of the region in theauthentication pattern. In some embodiments, the application furthercomprises a software module receiving a request to authenticate the 3Dobject. In some embodiments, the application further comprises asoftware module instructing a user to orient the front-facing camera ofthe mobile device in a fixed position relative to the object during thecapturing of the image data. In some embodiments, the variation of atleast one region in at least one of: brightness, position, size, shape,and color encode information in the authentication pattern.

A third aspect disclosed herein is a method of detecting spoofing of a3D object, using a 2D representation, in a mobile object authenticationprocess, the method comprising: capturing, via a front-facing camera ofa mobile device, image data of the 3D object while displaying, via afront-facing screen of the mobile device, an authentication patterncomprising a plurality of regions, wherein at least one of the regionsvaries in at least one of: brightness, position, size, shape, and colorover time causing a variance of lighting effects which create highlightsand shadows on the 3D object over time; using the image data and theauthentication pattern to determine a current spatial characteristic ofthe 3D object; and determining if spoofing of the 3D object, using a 2Drepresentation, is attempted in the mobile authentication process bycomparing the current spatial characteristic of the 3D object with astored reference spatial characteristic of the 3D object.

In some embodiments, the 3D object comprises a face, a palm (palmprint), a finger (fingerprint), or an ear. In some embodiments, the 2Drepresentation comprises a photograph of the 3D object. In someembodiments, the image data comprises a plurality of photographs of the3D object. In some embodiments, the image data comprises a video of the3D object. In some embodiments, the authentication pattern comprises aplurality of images. In some embodiments, the authentication patterncomprises a video. In some embodiments, the plurality of regions arearranged in two or more vertical or horizontal bands in theauthentication pattern. In some embodiments, the plurality of regionsare arranged in a horizontal band across the top or bottom of thescreen, or in a vertical band across the left or right side of thescreen in the authentication pattern. In some embodiments, theauthentication pattern comprises variation of at least one region in atleast one of: brightness, position, size, shape, and color, to form aregular pulse or a random pulse in the authentication pattern. In someembodiments, at least one of the regions varies in position over time toform a translation or rotation of the region in the authenticationpattern. In some embodiments, at least one of the regions varies in sizeover time to form a contraction or expansion of the region in theauthentication pattern. In some embodiments, further comprisingreceiving a request to authenticate the 3D object. In some embodiments,further comprising instructing a user to orient the front-facing cameraof the mobile device in a fixed position relative to the object duringthe capturing of the image data. In some embodiments, the variation ofat least one region in at least one of: brightness, position, size,shape, and color, encode information in the authentication pattern.

A fourth aspect provided herein is a mobile device comprising: afront-facing camera, a front-facing screen, at least one processor, amemory, an operating system configured to perform executableinstructions, and a computer program including instructions executableby the at least one processor to run an application for recognizing aclass or a within-class identity of a 3D object, solely or incombination with other mobile processes of object detection and identityrecognition, the application comprising: a software module capturing,via the front-facing camera, image data of the 3D object whiledisplaying, via the front-facing screen, an identification patterncomprising a plurality of regions, wherein at least one of the regionsvaries in at least one of: brightness, position, size, shape, and colorover time causing a variance of lighting effects which create highlightsand shadows on the 3D object over time; a software module using theimage data and the identification pattern to determine a current spatialcharacteristic of the 3D object; and a software module determining theclass, or the within-class identity of the 3D object, solely or incombination with other mobile processes of object detection and identityrecognition by comparing the current spatial characteristic of the 3Dobject with a stored reference spatial characteristic of the 3D object.

In some embodiments, the 3D object comprises a face, a palm (palmprint), a finger (fingerprint), or an ear. In some embodiments, theimage data comprises a plurality of photographs of the 3D object. Insome embodiments, the image data comprises a video of the 3D object. Insome embodiments, the identification pattern comprises a plurality ofimages. In some embodiments, the identification pattern comprises avideo. In some embodiments, the plurality of regions are arranged in twoor more vertical or horizontal bands in the identification pattern. Insome embodiments, the plurality of regions are arranged in a horizontalband across the top or bottom of the screen, or in a vertical bandacross the left or right side of the screen in the identificationpattern. In some embodiments, the identification pattern comprisesvariation of at least one region in at least one of: brightness,position, size, shape, and color to form a regular pulse or a randompulse in the identification pattern. In some embodiments, at least oneof the regions varies in position over time to form a translation orrotation of the region in the identification pattern. In someembodiments, at least one of the regions varies in size over time toform a contraction or expansion of the region in the identificationpattern. In some embodiments, the application further comprises asoftware module receiving a request to recognize the class, or thewithin-class identity of the 3D object. In some embodiments, theapplication further comprises a software module instructing a user toorient the front-facing camera of the mobile device in a fixed positionrelative to the object during the capturing of the image data. In someembodiments, the variation of at least one region in at least one of:brightness, position, size, shape, and color encode information in theidentification pattern.

A fifth aspect provided herein is a system for recognizing a class or awithin-class identity of a 3D object, solely or in combination withother mobile processes of object detection and identity recognition, thesystem comprising: a mobile device comprising a front-facing camera, afront-facing screen, at least one processor, a memory; and a servercomprising at least one processor and a memory: the mobile deviceconfigured to: capture, via the front-facing camera, image data of the3D object while displaying, via the front-facing screen, anidentification pattern comprising a plurality of regions, wherein atleast one of the regions varies in at least one of: brightness,position, size, shape, and color over time causing a variance oflighting effects which create highlights and shadows on the 3D objectover time; and transmit the image data and the identification pattern tothe server; the server configured to: receive the image data and theidentification pattern from the mobile device; use the image data andthe identification pattern to determine a current spatial characteristicof the 3D object; determine the class, or the within-class identity ofthe 3D object, solely or in combination with other mobile processes ofobject detection and identity recognition, by comparing the currentspatial characteristic of the 3D object with a stored reference spatialcharacteristic of the 3D object; and transmit the class, or thewithin-class identity of the 3D object to the mobile device.

In some embodiments, the 3D object comprises a face, a palm (palmprint), a finger (fingerprint), or an ear. In some embodiments, theimage data comprises a plurality of photographs of the 3D object. Insome embodiments, the image data comprises a video of the 3D object. Insome embodiments, the identification pattern comprises a plurality ofimages. In some embodiments, the identification pattern comprises avideo. In some embodiments, the plurality of regions are arranged in twoor more vertical or horizontal bands in the identification pattern. Insome embodiments, the plurality of regions are arranged in a horizontalband across the top or bottom of the screen, or in a vertical bandacross the left or right side of the screen in the identificationpattern. In some embodiments, the identification pattern comprisesvariation of at least one region in at least one of: brightness,position, size, shape, and color to form a regular pulse or a randompulse in the identification pattern. In some embodiments, at least oneof the regions varies in position over time to form a translation orrotation of the region in the identification pattern. In someembodiments, at least one of the regions varies in size over time toform a contraction or expansion of the region in the identificationpattern. In some embodiments, the application further comprises asoftware module receiving a request to determine a class or within-classidentity of the 3D object. In some embodiments, the application furthercomprises a software module instructing a user to orient thefront-facing camera of the mobile device in a fixed position relative tothe object during the capturing of the image data. In some embodiments,the variation of at least one region in at least one of: brightness,position, size, shape, and color encode information in theidentification pattern.

A sixth aspect provided herein is a method of recognizing a class orwithin-class identity of a 3D object, solely or in combination withother mobile processes of object detection and identity recognition, themethod comprising: capturing, via a front-facing camera of a mobiledevice, image data of the 3D object while displaying, via a front-facingscreen of the mobile device, an identification pattern comprising aplurality of regions, wherein at least one of the regions varies in atleast one of: brightness, position, size, shape, and color over timecausing a variance of lighting effects which create highlights andshadows on the 3D object over time; using the image data and theidentification pattern to determine a current spatial characteristic ofthe 3D object; and determining the class, or the within-class identityof a 3D object of the 3D object, solely or in combination with othermobile processes of object detection and identity recognition, bycomparing the current spatial characteristic of the 3D object with astored reference spatial characteristic of the 3D object.

In some embodiments, the 3D object comprises a face, a palm (palmprint), a finger (fingerprint), or an ear. In some embodiments, theimage data comprises a plurality of photographs of the 3D object. Insome embodiments, the image data comprises a video of the 3D object. Insome embodiments, the identification pattern comprises a plurality ofimages. In some embodiments, the identification pattern comprises avideo. In some embodiments, the plurality of regions are arranged in twoor more vertical or horizontal bands in the identification pattern. Insome embodiments, the plurality of regions are arranged in a horizontalband across the top or bottom of the screen, or in a vertical bandacross the left or right side of the screen in the identificationpattern. In some embodiments, the identification pattern comprisesvariation of at least one region in at least one of: brightness,position, size, shape, and color, to form a regular pulse or a randompulse in the identification pattern. In some embodiments, at least oneof the regions varies in position over time to form a translation orrotation of the region in the identification pattern. In someembodiments, at least one of the regions varies in size over time toform a contraction or expansion of the region in the identificationpattern. In some embodiments, further comprising receiving a request torecognize a class or within-class identity of the 3D object. In someembodiments, further comprising instructing a user to orient thefront-facing camera of the mobile device in a fixed position relative tothe object during the capturing of the image data. In some embodiments,the variation of at least one region in at least one of: brightness,position, size, shape, and color, encode information in theidentification pattern.

In some embodiments, the plurality of regions comprises 2 regions to 50regions. In some embodiments, the plurality of regions comprises atleast 2 regions. In some embodiments, the plurality of regions comprisesat most 50 regions. In some embodiments, the plurality of regionscomprises 2 regions to 3 regions, 2 regions to 4 regions, 2 regions to 5regions, 2 regions to 10 regions, 2 regions to 15 regions, 2 regions to20 regions, 2 regions to 25 regions, 2 regions to 30 regions, 2 regionsto 35 regions, 2 regions to 40 regions, 2 regions to 50 regions, 3regions to 4 regions, 3 regions to 5 regions, 3 regions to 10 regions, 3regions to 15 regions, 3 regions to 20 regions, 3 regions to 25 regions,3 regions to 30 regions, 3 regions to 35 regions, 3 regions to 40regions, 3 regions to 50 regions, 4 regions to 5 regions, 4 regions to10 regions, 4 regions to 15 regions, 4 regions to 20 regions, 4 regionsto 25 regions, 4 regions to 30 regions, 4 regions to 35 regions, 4regions to 40 regions, 4 regions to 50 regions, 5 regions to 10 regions,5 regions to 15 regions, 5 regions to 20 regions, 5 regions to 25regions, 5 regions to 30 regions, 5 regions to 35 regions, 5 regions to40 regions, 5 regions to 50 regions, 10 regions to 15 regions, 10regions to 20 regions, 10 regions to 25 regions, 10 regions to 30regions, 10 regions to 35 regions, 10 regions to 40 regions, 10 regionsto 50 regions, 15 regions to 20 regions, 15 regions to 25 regions, 15regions to 30 regions, 15 regions to 35 regions, 15 regions to 40regions, 15 regions to 50 regions, 20 regions to 25 regions, 20 regionsto 30 regions, 20 regions to 35 regions, 20 regions to 40 regions, 20regions to 50 regions, 25 regions to 30 regions, 25 regions to 35regions, 25 regions to 40 regions, 25 regions to 50 regions, 30 regionsto 35 regions, 30 regions to 40 regions, 30 regions to 50 regions, 35regions to 40 regions, 35 regions to 50 regions, or 40 regions to 50regions. In some embodiments, the plurality of regions comprises 2regions, 3 regions, 4 regions, 5 regions, 10 regions, 15 regions, 20regions, 25 regions, 30 regions, 35 regions, 40 regions, 50 regions, ormore, including increments therein.

In some embodiments, a region comprises a percentage of the area of thescreen of the mobile device of 0% to 99%. In some embodiments, a regioncomprises a percentage of the area of the screen of the mobile device ofat least 0%. In some embodiments, a region comprises a percentage of thearea of the screen of the mobile device of at most 99%. In someembodiments, a region comprises a percentage of the area of the screenof the mobile device of 0% to 1%, 0% to 10%, 0% to 20%, 0% to 30%, 0% to40%, 0% to 50%, 0% to 60%, 0% to 70%, 0% to 80%, 0% to 90%, 0% to 99%,1% to 10%, 1% to 20%, 1% to 30%, 1% to 40%, 1% to 50%, 1% to 60%, 1% to70%, 1% to 80%, 1% to 90%, 1% to 99%, 10% to 20%, 10% to 30%, 10% to40%, 10% to 50%, 10% to 60%, 10% to 70%, 10% to 80%, 10% to 90%, 10% to99%, 20% to 30%, 20% to 40%, 20% to 50%, 20% to 60%, 20% to 70%, 20% to80%, 20% to 90%, 20% to 99%, 30% to 40%, 30% to 50%, 30% to 60%, 30% to70%, 30% to 80%, 30% to 90%, 30% to 99%, 40% to 50%, 40% to 60%, 40% to70%, 40% to 80%, 40% to 90%, 40% to 99%, 50% to 60%, 50% to 70%, 50% to80%, 50% to 90%, 50% to 99%, 60% to 70%, 60% to 80%, 60% to 90%, 60% to99%, 70% to 80%, 70% to 90%, 70% to 99%, 80% to 90%, 80% to 99%, or 90%to 99%. In some embodiments, a region comprises a percentage of the areaof the screen of the mobile device of 0%, 1%, 10%, 20%, 30%, 40%, 50%,60%, 70%, 80%, 90%, or 99%.

In some embodiments, a region exhibits a percentage of the mobiledevice's brightness capability of 0% to 100%. In some embodiments, aregion exhibits a percentage of the mobile device's brightnesscapability of at least 0%. In some embodiments, a region exhibits apercentage of the mobile device's brightness capability of at most 100%.In some embodiments, a region exhibits a percentage of the mobiledevice's brightness capability of 0% to 1%, 0% to 10%, 0% to 20%, 0% to30%, 0% to 40%, 0% to 50%, 0% to 60%, 0% to 70%, 0% to 80%, 0% to 90%,0% to 100%, 1% to 10%, 1% to 20%, 1% to 30%, 1% to 40%, 1% to 50%, 1% to60%, 1% to 70%, 1% to 80%, 1% to 90%, 1% to 100%, 10% to 20%, 10% to30%, 10% to 40%, 10% to 50%, 10% to 60%, 10% to 70%, 10% to 80%, 10% to90%, 10% to 100%, 20% to 30%, 20% to 40%, 20% to 50%, 20% to 60%, 20% to70%, 20% to 80%, 20% to 90%, 20% to 100%, 30% to 40%, 30% to 50%, 30% to60%, 30% to 70%, 30% to 80%, 30% to 90%, 30% to 100%, 40% to 50%, 40% to60%, 40% to 70%, 40% to 80%, 40% to 90%, 40% to 100%, 50% to 60%, 5% to70%, 50% to 80%, 50% to 90%, 50% to 100%, 60% to 70%, 60% to 80%, 60% to90%, 60% to 100%, 70% to 80%, 70% to 90%, 70% to 100%, 80% to 90%, 80%to 100%, or 90% to 100%. In some embodiments, a region exhibits apercentage of the mobile device's brightness capability of 0%, 1%, 10%,20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, or 100%, including incrementstherein.

In some embodiments, a region exhibits a shape comprising a circle, anoval, an arch, an ellipse, a triangle, a square, a polygon, an amorphousshape, or any combination thereof. In some embodiments, a regionexhibits a color comprising alice blue, antique white, aqua, aquamarine,azure, beige, bisque, black, blanched almond, blue, blue violet, brown,burly wood, cadet blue, chartreuse, chocolate, coral, cornflower blue,cornsilk, crimson, cyan, dark blue, dark cyan, dark golden rod, darkgray, dark grey, dark green, dark khaki, dark magenta, dark olive green,dark orange, dark orchid, dark red, dark salmon, dark sea green, darkslate blue, dark slate gray, dark turquoise, dark violet, deep pink,deep sky blue, dim grey, dodger blue, fire brick, floral white, forestgreen, fuchsia, gainsboro, ghost white, gold, golden rod, gray, green,green yellow, honey dew, hot pink, indian red, indigo, ivory, khaki,lavender, lavender blush, lawn green, lemon chiffon, light blue, lightcoral, light cyan, light goldenrod yellow, light grey, light green,light pink, light salmon, light sea green, light sky blue, light slategray, light slate grey, light steel blue, light yellow, lime, limegreen, linen, magenta, maroon, medium aqua marine, medium blue, mediumorchid, medium purple, medium sea green, medium slate blue, mediumspring green, medium turquoise, medium violet red, midnight blue, mintcream, misty rose, moccasin, navajo white, navy, old lace, olive, olivedrab, orange, orange red, orchid, pale golden rod, pale green, paleturquoise, pale violet red, papaya whip, peach puff, peru, pink, plum,powder blue, purple, rebecca purple, red, rosy brown, royal blue, saddlebrown, salmon, sandy brown, sea green, sea shell, sienna, silver, skyblue, slate blue, slate grey, snow, spring green, steel blue, tan, teal,thistle, tomato, turquoise, violet, wheat, white, white smoke, yellow,yellow green, or any combination thereof.

In some embodiments, the number of images in the authentication patternis 2 to 10,000. In some embodiments, the number of images in theauthentication pattern is at least 2. In some embodiments, the number ofimages in the authentication pattern is at most 10,000. In someembodiments, the number of images in the authentication pattern is 2 to5, 2 to 10, 2 to 20, 2 to 50, 2 to 100, 2 to 200, 2 to 500, 2 to 1,000,2 to 2,000, 2 to 5,000, 2 to 10,000, 5 to 10, 5 to 20, 5 to 50, 5 to100, 5 to 200, 5 to 500, 5 to 1,000, 5 to 2,000, 5 to 5,000, 5 to10,000, 10 to 20, 10 to 50, 10 to 100, 10 to 200, 10 to 500, 10 to1,000, 10 to 2,000, 10 to 5,000, 10 to 10,000, 20 to 50, 20 to 100, 20to 200, 20 to 500, 20 to 1,000, 20 to 2,000, 20 to 5,000, 20 to 10,000,50 to 100, 50 to 200, 50 to 500, 50 to 1,000, 50 to 2,000, 50 to 5,000,50 to 10,000, 100 to 200, 100 to 500, 100 to 1,000, 100 to 2,000, 100 to5,000, 100 to 10,000, 200 to 500, 200 to 1,000, 200 to 2,000, 200 to5,000, 200 to 10,000, 500 to 1,000, 500 to 2,000, 500 to 5,000, 500 to10,000, 1,000 to 2,000, 1,000 to 5,000, 1,000 to 10,000, 2,000 to 5,000,2,000 to 10,000, or 5,000 to 10,000. In some embodiments, the number ofimages in the authentication pattern is 2, 5, 10, 20, 50, 100, 200, 500,1,000, 2,000, 5,000, or 10,000, including increments therein.

In some embodiments, the number of photographs of the 3D object thatcomprise the image data is 2 to 10,000. In some embodiments, the numberof photographs of the 3D object that comprise the image data is at least2. In some embodiments, the number of photographs of the 3D object thatcomprise the image data is at most 10,000. In some embodiments, thenumber of photographs of the 3D object that comprise the image data is 2to 5, 2 to 10, 2 to 20, 2 to 50, 2 to 100, 2 to 200, 2 to 500, 2 to1,000, 2 to 2,000, 2 to 5,000, 2 to 10,000, 5 to 10, 5 to 20, 5 to 50, 5to 100, 5 to 200, 5 to 500, 5 to 1,000, 5 to 2,000, 5 to 5,000, 5 to10,000, 10 to 20, 10 to 50, 10 to 100, 10 to 200, 10 to 500, 10 to1,000, 10 to 2,000, 10 to 5,000, 10 to 10,000, 20 to 50, 20 to 100, 20to 200, 20 to 500, 20 to 1,000, 20 to 2,000, 20 to 5,000, 20 to 10,000,50 to 100, 50 to 200, 50 to 500, 50 to 1,000, 50 to 2,000, 50 to 5,000,50 to 10,000, 100 to 200, 100 to 500, 100 to 1,000, 100 to 2,000, 100 to5,000, 100 to 10,000, 200 to 500, 200 to 1,000, 200 to 2,000, 200 to5,000, 200 to 10,000, 500 to 1,000, 500 to 2,000, 500 to 5,000, 500 to10,000, 1,000 to 2,000, 1,000 to 5,000, 1,000 to 10,000, 2,000 to 5,000,2,000 to 10,000, or 5,000 to 10,000. In some embodiments, the number ofphotographs of the 3D object that comprise the image data is 2, 5, 10,20, 50, 100, 200, 500, 1,000, 2,000, 5,000, or 10,000, includingincrements therein.

BRIEF DESCRIPTION OF THE DRAWINGS

A better understanding of the features and advantages of the presentsubject matter will be obtained by reference to the following detaileddescription that sets forth illustrative embodiments and theaccompanying drawings of which:

FIG. 1 shows an illustration of an exemplary device for detectingspoofing of a 3D object, using a 2D representation, in a mobile objectauthentication process;

FIG. 2A shows an illustration of a first exemplary image of anauthentication pattern comprising two horizontally arrayed regions;

FIG. 2B shows an illustration of a second exemplary image of anauthentication pattern comprising two vertically arrayed regions;

FIG. 2C shows an illustration of a third exemplary image of anauthentication pattern comprising four horizontally arrayed regions;

FIG. 2D shows an illustration of a fourth exemplary image of anauthentication pattern comprising four vertically arrayed regions;

FIG. 2E shows an illustration of a fifth exemplary image of anauthentication pattern comprising three regions arranged in verticalbands;

FIG. 2F shows an illustration of a sixth exemplary image of anauthentication pattern comprising three regions arranged in horizontalbands;

FIG. 2G shows an illustration of a seventh exemplary image of anauthentication pattern comprising a plurality of horizontally arrayedregions;

FIG. 2H shows an illustration of a eighth exemplary image of anauthentication pattern comprising a plurality of vertically arrayedregions;

FIG. 3A shows an illustration of an exemplary first authenticationpattern comprising a rotation of a region;

FIG. 3B shows an illustration of an exemplary second authenticationpattern comprising a rotation of a plurality of regions;

FIG. 4A shows an illustration of an exemplary first image data,displaying the highlights and shadows on an object resulting from theauthentication image in FIG. 2A;

FIG. 4B shows an illustration of an exemplary first image data,displaying the highlights and shadows on an object resulting from theauthentication image in FIG. 2B;

FIG. 5A shows an illustration of an exemplary first image data,displaying the highlights and shadows on a human face resulting from theauthentication image in FIG. 2A;

FIG. 5B shows an illustration of an exemplary first image data,displaying the highlights and shadows on a human face resulting from theauthentication image in FIG. 2B;

FIG. 6A shows a top view illustration of the exemplary authenticationimage in FIG. 2E causing a variance of lighting effects which createhighlights and shadows on a human face;

FIG. 6B shows a top view illustration of the exemplary authenticationimage in FIG. 2F causing a variance of lighting effects which createhighlights and shadows on a human face;

FIG. 6C shows top view illustrations of the exemplary authenticationimages in FIGS. 2E and 2F causing a variance of lighting effects whichcreate highlights and shadows on a human face;

FIG. 6D shows front view illustrations of the exemplary authenticationimages in FIGS. 2E and 2F causing a variance of lighting effects whichcreate highlights and shadows on a human face;

FIG. 7A shows illustrations of exemplary highlights and shadows on ahuman face as a result of brightness applied from a variety ofdirections;

FIG. 7B shows exemplary pictures of highlights and shadows on a humanface as a result of brightness applied from a variety of directions;

FIG. 8 shows a non-limiting schematic diagram of a digital processingdevice; in this case, a device with one or more CPUs, a memory, acommunication interface, and a display;

FIG. 9 shows a non-limiting schematic diagram of a web/mobileapplication provision system; in this case, a system providingbrowser-based and/or native mobile user interfaces; and

FIG. 10 shows a non-limiting schematic diagram of a cloud-basedweb/mobile application provision system; in this case, a systemcomprising an elastically load balanced, auto-scaling web server andapplication server resources as well synchronously replicated databases.

DETAILED DESCRIPTION OF THE DRAWINGS Terms and Definitions

Unless otherwise defined, all technical terms used herein have the samemeaning as commonly understood by one of ordinary skill in the art towhich this disclosure belongs.

As used herein, the singular forms “a,” “an,” and “the” include pluralreferences unless the context clearly dictates otherwise. Any referenceto “or” herein is intended to encompass “and/or” unless otherwisestated.

As used herein, the term “about” refers to an amount that is near thestated amount by 10%, 5%, or 1%, including increments therein.

As used herein, the term “front-facing camera” refers to a feature ofcameras, mobile phones, smartphones, tablets and similar mobile devicesthat allows a user to take self-portrait, photograph, or video whilelooking at the display of the device.

As used herein, the term “3D” refers to having a length, a breadth, anda depth.

As used herein, the term “2D” refers to having a length and a breadth, alength and a depth, or a breadth and a depth, of much greater magnitudein relation to any third dimension of the object as to the 3D object forwhich it is presented as a spoof.

While preferred embodiments of the present subject matter have beenshown and described herein, it will be obvious to those skilled in theart that such embodiments are provided by way of example only. Numerousvariations, changes, and substitutions will now occur to those skilledin the art without departing from the disclosure. It should beunderstood that various alternatives to the embodiments of the subjectmatter described herein may be employed in practicing the disclosure.

Devices for Detecting Spoofing of a 3D Object

Provided herein, per FIG. 1, is a mobile device 110 for detectingspoofing of a 3D object 101 comprising a front-facing screen 111, and afront-facing camera 112; at least one processor; a memory, an operatingsystem configured to perform executable instructions; and a computerprogram including instructions executable by the at least one processorto run an application for detecting spoofing of a 3D object 101, using a2D representation, in a mobile object authentication process. In someembodiments, the application comprises: a software module capturing, viathe front-facing camera 112, image data of the 3D object 101 whiledisplaying, via the front-facing screen 111, an authentication patterncomprising a plurality of regions, wherein at least one of the regionsvaries in at least one of: brightness, position, size, shape, and colorover time causing a variance of lighting effects which create highlightsand shadows on the 3D object 101 over time. In some embodiments, themobile device 110 further comprises a software module using the imagedata and the authentication pattern to determine a current spatialcharacteristic of the 3D object 101, and a software module determiningif spoofing of the 3D object 101, using a 2D representation, isattempted in the mobile authentication process, by comparing the currentspatial characteristic of the 3D object 101 with a stored referencespatial characteristic of the 3D object 101.

In some embodiments, the 3D object 101 comprises a face, a palm (palmprint), a finger (fingerprint), or an ear. In some embodiments, the 3Dobject 101 comprises a human face. In some embodiments, the 2Drepresentation comprises a photograph of the 3D object 101. In someembodiments, the image data comprises a plurality of photographs of the3D object 101. In some embodiments, the image data comprises a video ofthe 3D object 101. In some embodiments, the authentication patterncomprises a plurality of images. In some embodiments, the authenticationpattern comprises a video. In some embodiments, the plurality of regionsis arranged in two or more vertical or horizontal bands in theauthentication pattern. In some embodiments, the plurality of regionsare arranged in a horizontal band across the top or bottom of thescreen, or in a vertical band across the left or right side of thescreen in the authentication pattern. In some embodiments, theauthentication pattern comprises variation of at least one region in atleast one of: brightness, position, size, shape, and color to form aregular pulse or a random pulse in the authentication pattern. In someembodiments, at least one of the regions varies in position over time toform a translation or rotation of the region in the authenticationpattern. In some embodiments, at least one of the regions varies in sizeover time to form a contraction or expansion of the region in theauthentication pattern. In some embodiments, the application furthercomprises a software module receiving a request to authenticate the 3Dobject 101. In some embodiments, the application further comprises asoftware module instructing a user to orient the front-facing camera ofthe mobile device in a fixed position relative to the object during thecapturing of the image data. In some embodiments, the variation of atleast one region in at least one of: brightness, position, size, shape,and color encode information in the authentication pattern.

Authentication Patterns

FIGS. 2A to 211, shows illustrations of exemplary images of theplurality of images which comprises the authentication pattern, whereinthe authentication pattern comprises a plurality of regions that differin brightness, color, or any combination thereof.

In some embodiments, per FIG. 2A, the plurality of regions comprises ahigh brightness region 231 and a low brightness region 232, that arearranged in two vertical bands. In some embodiments, per FIG. 2B, theplurality of regions comprises a high brightness region 231 and a lowbrightness region 232, that are arranged in two horizontal bands. Insome embodiments, the high brightness region 231 is displayed on theleft, right, top or bottom of the low brightness region 232. In someembodiments, per FIG. 2C, the plurality of regions comprises two highbrightness regions 231 and two low brightness regions 232 that arearranged in four alternating vertical bands. In some embodiments, perFIG. 2D, the plurality of regions comprises two high brightness regions231 and two low brightness regions 232 that are arranged in fouralternating horizontal bands. In some embodiments, per FIG. 2G, theplurality of regions comprises a plurality of high brightness regions231 and a plurality of low brightness regions 232 that are arranged inalternating horizontal, or vertical, bands.

In some embodiments, per FIG. 2E, the plurality of regions comprises twohorizontal bands of high brightness regions 231 across the top andbottom of the screen, and a single horizontal band of a low brightnessregion 232 across the middle of the screen. In some embodiments, perFIG. 2F, the plurality of regions comprises vertical or horizontal bandsof high brightness regions 231 along the left and right sides of thescreen, and a single vertical band of a low brightness region 232 alongthe middle of the screen. In some embodiments, per FIG. 2G, theplurality of regions comprises a plurality of randomly shaped andpositioned, high brightness regions 231 and low brightness regions 232.

In some embodiments the authentication pattern comprises a variation ofat least one region in at least one of: brightness, position, size,shape, and color to form a regular pulse or a random pulse. In someembodiments, per FIGS. 3A and 3B, at least one of the high brightnessregions 331 and low brightness regions 332 vary in position over time toform a translation or rotation of the region in the authenticationpattern. In some embodiments, at least one of the regions varies in sizeover time, to form a contraction or expansion of the region in theauthentication pattern.

Methods for Detecting Spoofing of a 3D Object

Provided herein, per FIGS. 4A and 4B is a method of detecting spoofingof a 3D object 410, using a 2D representation 420 a, 420 b, in a mobileobject authentication process, the method comprising: capturing, via afront-facing camera of a mobile device, image data of the 3D object 410while displaying, via a front-facing screen of the mobile device, anauthentication pattern comprising a plurality of regions, wherein atleast one of the regions varies in at least one of: brightness,position, size, shape, and color over time causing a variance oflighting effects which create highlights and shadows on the 3D object410 over time; using the image data and the authentication pattern todetermine a current spatial characteristic of the 3D object 410; anddetermining if spoofing of the 3D object 410, using a 2D representation420 a, 420 b, is attempted in the mobile authentication process bycomparing the current spatial characteristic of the 3D object 410 with astored reference spatial characteristic of the 3D object 410.

In some embodiments an authentication pattern comprises a plurality ofregions, wherein at least one of the regions varies in at least one of:brightness, position, size, shape, and color over time causing avariance of lighting effects which create highlights and shadows on the3D object 410 over time, per FIGS. 4A and 4B. In some embodiments theauthentication pattern comprises a plurality of images. In the casewherein the regions in an image of the authentication pattern comprise asingle high brightness region displayed on the left side of thefront-facing-screen, and a low high brightness region displayed on theright side of the front-facing-screen, as per FIG. 2A, the highlightsand shadows on the 3D object 410, are seen in the exemplary 2Drepresentation 420 a in FIG. 4A. In the case wherein the regions in animage of the authentication pattern comprise a single high brightnessregion displayed on the bottom of the front-facing-screen, and a lowhigh brightness region displayed on the top of the front-facing-screen,as per FIG. 2B, the highlights and shadows on the 3D object 410, areseen in the exemplary 2D representation 420 b in FIG. 4B.

The differences between the 2D representations 420 a, 420 b of the 3Dobject 410, may be used to determine a spatial characteristic of the 3Dobject 410, and to determine if spoofing of the 3D object 410, using a2D representation 420 a, 420 b, is attempted in the mobileauthentication process, by comparing the current spatial characteristicof the 3D object 410 with a stored reference spatial characteristic ofthe 3D object 410.

Once a current spatial characteristic of the 3D object 410 from theimage data and the authentication pattern is determined to match astored reference spatial characteristic of the 3D object 410, an accessmay be granted if no spoofing is detected, or block access to the userif spoofing is detected. An authority may additionally be alerted withinformation related to the time, location, device, account, or anycombination thereof associated with the spoofing attempt.

In some embodiments, the authentication pattern comprises a plurality ofregions, wherein at least one of the regions varies in at least one of:brightness, position, size, shape, and color over time causing avariance of lighting effects which create highlights and shadows on the3D object 410 over time, and wherein the variation of at least oneregion in at least one of: brightness, position, size, shape, and color,encodes information in the authentication pattern. In some embodiments,the encoded information comprises encoded information corresponding tothe user, the object, the authentication attempt, or any combinationthereof. In some embodiments, determination that highlights and shadowson the 3D object 410, captured by the 2D representation 420 a, 420 b,correlate with the information encoded within the authenticationpattern, serves as an additional factor of authentication and/orsecurity.

In some embodiments, per FIGS. 5A and 5B, the object comprises a humanface 510 wherein the front-facing camera captures the 2D representation520 a, 520 b of the human face 510 to detect spoofing. In someembodiments, per FIG. 5A, the authentication pattern comprises aplurality of images, wherein each image of the authentication patterncomprises a plurality of regions, and wherein at least one of theregions varies in at least one of: brightness, position, size, shape,and color over time causing a variance of lighting effects which createhighlights and shadows on the 3D object 510 over time. In the casewherein the plurality of regions in the authentication pattern comprisesa single low brightness region displayed on the left side of thefront-facing-screen, and a single high brightness region displayed onthe right side of the front-facing-screen, as per FIG. 2A, thehighlights and shadows on the human face 510, are seen in the exemplary2D representation 520 a in FIG. 5A. In the case wherein the plurality ofregions in the authentication pattern comprises a single low brightnessregion displayed on the top side of the front-facing-screen, and asingle high brightness region displayed on the bottom side of thefront-facing-screen, as per FIG. 2B, the highlights and shadows on thehuman face 510, are seen in the exemplary 2D representation 520 b inFIG. 5B.

The differences between the 2D representations 520 a, 520 b of the humanface 510, may be used to determine a spatial characteristic of the humanface 510, and to determine if spoofing of the human face 510, using a 2Drepresentation 520 a, 520 b, is attempted in the mobile authenticationprocess by comparing the current spatial characteristic of the humanface 510 with a stored reference spatial characteristic of the humanface 510.

Once a current spatial characteristic of the human face 510 from theimage data and the authentication pattern is determined to match astored reference spatial characteristic of the human face 510, an accessmay be granted if no spoofing is detected, or block access to the userif spoofing is detected. An authority may additionally be alerted withinformation related to the time, location, device, account, or anycombination thereof associated with the spoofing attempt.

In some embodiments, per FIGS. 6A, 6B, and 6C, the object comprises ahuman face 610 and the front-facing camera captures the 2Drepresentation of the human face 610 to detect spoofing. In someembodiments, the authentication pattern comprises a plurality of images,wherein an image comprises a plurality of regions, and wherein at leastone of the regions varies in at least one of: brightness, position,size, shape, and color over time causing a variance of lighting effectswhich create highlights and shadows on the human face 610 over time. Itcan be seen, per FIG. 6A, that an image of a first authenticationpattern 620 a comprising a two high brightness regions 601 displayedalong the top and bottom of the front-facing-screen, and a single lowbrightness region 602 displayed along the middle of thefront-facing-screen, as per FIG. 2E casts certain highlights and shadowson the human face 610. By contrast, an image of a second authenticationpattern 620 b, per FIG. 6B, comprising a two high brightness regions 601displayed along the left and right sides of the front-facing-screen, anda single low brightness region 602 displayed along a middle band of thefront-facing-screen, as per FIG. 2F casts different highlights andshadows on the human face 610.

The differences between the 2D representations captured of the humanface 610, while the front-facing-screen displays the firstauthentication image 620 a and while the front-facing-screen displaysthe second authentication image 620 b, may be used to determine acurrent spatial characteristic of the human face 610, and to determineif spoofing of the human face 610, using a 2D representation, isattempted in the mobile authentication process by comparing the currentspatial characteristic of the human face 610 with a stored referencespatial characteristic of the human face 610.

Per FIG. 6D, it can be seen that if the object is in fact a human face610, and if the authentication pattern comprises high brightness regionsacross the top and bottom of the screen and the single horizontal bandof a low brightness region in the middle of the screen, as per FIG. 2E,the spatial characteristic of the human face 610 should exhibithighlights on the top of the head of the human face 610, and on the chinof the human face 610. Per FIG. 6D, it can also be seen that if theobject is in fact a human face 610, and if the authentication patterncomprises high brightness regions across the left and right sides of thescreen and the single horizontal band of a low brightness region acrossthe middle of the screen, as per FIG. 2F, the spatial characteristic ofthe human face 610 should exhibit highlights on the left and right sidesof the head of the human face 610.

Once a current spatial characteristic of the human face 610 from theimage data and the authentication pattern is determined to match astored reference spatial characteristic of the human face 610, an accessmay be granted if no spoofing is detected, or block access to the userif spoofing is detected. An authority may additionally be alerted withinformation related to the time, location, device, account, or anycombination thereof associated with the spoofing attempt.

Systems for Detecting Spoofing of a 3D Object

Provided herein is a system for detecting spoofing of a 3D object, usinga 2D representation, in a mobile object authentication process, thesystem comprising: a mobile device comprising a front-facing camera, afront-facing screen, at least one processor, a memory; and a servercomprising at least one processor and a memory: the mobile deviceconfigured to: capture, via the front-facing camera, image data of the3D object while displaying, via the front-facing screen, anauthentication pattern comprising a plurality of regions, wherein atleast one of the regions varies in at least one of: brightness,position, size, shape, and color over time causing a variance oflighting effects which create highlights and shadows on the 3D objectover time; and transmit the image data and the authentication pattern tothe server; the server configured to: receive the image data and theauthentication pattern from the mobile device; use the image data andthe authentication pattern to determine a current spatial characteristicof the 3D object; determine if spoofing of the 3D object, using a 2Drepresentation, is attempted in the mobile authentication process bycomparing the current spatial characteristic of the 3D object with astored reference spatial characteristic of the 3D object; and transmit aresult spoofing result to the mobile device.

Digital Processing Device

In some embodiments, the platforms, systems, media, and methodsdescribed herein include a digital processing device, or use of thesame. In further embodiments, the digital processing device includes oneor more hardware central processing units (CPUs) or general purposegraphics processing units (GPGPUs) that carry out the device'sfunctions. In still further embodiments, the digital processing devicefurther comprises an operating system configured to perform executableinstructions. In some embodiments, the digital processing device isoptionally connected to a computer network. In further embodiments, thedigital processing device is optionally connected to the Internet suchthat it accesses the World Wide Web. In still further embodiments, thedigital processing device is optionally connected to a cloud computinginfrastructure. In other embodiments, the digital processing device isoptionally connected to an intranet. In other embodiments, the digitalprocessing device is optionally connected to a data storage device.

In accordance with the description herein, suitable digital processingdevices include, by way of non-limiting examples, server computers,desktop computers, laptop computers, notebook computers, sub-notebookcomputers, netbook computers, netpad computers, set-top computers, mediastreaming devices, handheld computers, Internet appliances, mobilesmartphones, tablet computers, personal digital assistants, video gameconsoles, and vehicles. Those of skill in the art will recognize thatmany smartphones are suitable for use in the system described herein.Those of skill in the art will also recognize that select televisions,video players, and digital music players with optional computer networkconnectivity are suitable for use in the system described herein.Suitable tablet computers include those with booklet, slate, andconvertible configurations, known to those of skill in the art.

In some embodiments, the digital processing device includes an operatingsystem configured to perform executable instructions. The operatingsystem is, for example, software, including programs and data, whichmanages the device's hardware and provides services for execution ofapplications. Those of skill in the art will recognize that suitableserver operating systems include, by way of non-limiting examples,FreeBSD, OpenBSD, NetBSD, Linux, Apple® Mac OS X Server®, Oracle®Solaris®, Windows Server®, and Novell® NetWare®. Those of skill in theart will recognize that suitable personal computer operating systemsinclude, by way of non-limiting examples, Microsoft® Windows®, Apple®Mac OS X®, UNIX®, and UNIX-like operating systems such as GNU/Linux®. Insome embodiments, the operating system is provided by cloud computing.Those of skill in the art will also recognize that suitable mobile smartphone operating systems include, by way of non-limiting examples, Nokia®Symbian® OS, Apple® iOS®, Research In Motion® BlackBerry OS®, Google®Android®, Microsoft® Windows Phone® OS, Microsoft® Windows Mobile® OS,Linux®, and Palm® WebOS®. Those of skill in the art will also recognizethat suitable media streaming device operating systems include, by wayof non-limiting examples, Apple TV®, Roku®, Boxee®, Google TV®, GoogleChromecast®, Amazon Fire®, and Samsung® HomeSync®. Those of skill in theart will also recognize that suitable video game console operatingsystems include, by way of non-limiting examples, Sony® P53®, Sony®P54®, Microsoft® Xbox 360®, Microsoft Xbox One, Nintendo® Wii®,Nintendo® Wii U®, and Ouya®.

In some embodiments, the device includes a storage and/or memory device.The storage and/or memory device is one or more physical apparatusesused to store data or programs on a temporary or permanent basis. Insome embodiments, the device is volatile memory and requires power tomaintain stored information. In some embodiments, the device isnon-volatile memory and retains stored information when the digitalprocessing device is not powered. In further embodiments, thenon-volatile memory comprises flash memory. In some embodiments, thenon-volatile memory comprises dynamic random-access memory (DRAM). Insome embodiments, the non-volatile memory comprises ferroelectric randomaccess memory (FRAM). In some embodiments, the non-volatile memorycomprises phase-change random access memory (PRAM). In otherembodiments, the device is a storage device including, by way ofnon-limiting examples, CD-ROMs, DVDs, flash memory devices, magneticdisk drives, magnetic tapes drives, optical disk drives, and cloudcomputing based storage. In further embodiments, the storage and/ormemory device is a combination of devices such as those disclosedherein.

In some embodiments, the digital processing device includes a display tosend visual information to a user. In some embodiments, the display is aliquid crystal display (LCD). In further embodiments, the display is athin film transistor liquid crystal display (TFT-LCD). In someembodiments, the display is an organic light emitting diode (OLED)display. In various further embodiments, on OLED display is apassive-matrix OLED (PMOLED) or active-matrix OLED (AMOLED) display. Insome embodiments, the display is a plasma display. In other embodiments,the display is a video projector. In yet other embodiments, the displayis a head-mounted display in communication with the digital processingdevice, such as a VR headset. In further embodiments, suitable VRheadsets include, by way of non-limiting examples, HTC Vive, OculusRift, Samsung Gear VR, Microsoft HoloLens, Razer OSVR, FOVE VR, Zeiss VROne, Avegant Glyph, Freefly VR headset, and the like. In still furtherembodiments, the display is a combination of devices such as thosedisclosed herein.

In some embodiments, the digital processing device includes an inputdevice to receive information from a user. In some embodiments, theinput device is a keyboard. In some embodiments, the input device is apointing device including, by way of non-limiting examples, a mouse,trackball, track pad, joystick, game controller, or stylus. In someembodiments, the input device is a touch screen or a multi-touch screen.In other embodiments, the input device is a microphone to capture voiceor other sound input. In other embodiments, the input device is a videocamera or other sensor to capture motion or visual input. In furtherembodiments, the input device is a Kinect, Leap Motion, or the like. Instill further embodiments, the input device is a combination of devicessuch as those disclosed herein.

Referring to FIG. 8, in a particular embodiment, an exemplary digitalprocessing device 801 is programmed or otherwise configured to detectspoofing of a 3D object, using a 2D representation, in a mobile objectauthentication process. The digital processing device 801 can regulatevarious aspects of detecting spoofing of a 3D object of the presentdisclosure, such as, for example, capturing, via a front-facing cameraof a mobile device, image data of the 3D object while displaying, via afront-facing screen of the mobile device, an authentication pattern;using the image data and the authentication pattern to determine acurrent spatial characteristic of the 3D object; determining if spoofingof the 3D object, using a 2D representation, is attempted in the mobileauthentication process by comparing the current spatial characteristicof the 3D object with a stored reference spatial characteristic of the3D object; or transmit image data and authentication pattern to aserver. In this embodiment, the digital processing device 801 includes acentral processing unit (CPU, also “processor” and “computer processor”herein) 805, which can be a single core or multi core processor, or aplurality of processors for parallel processing. The digital processingdevice 801 also includes memory or memory location 810 (e.g.,random-access memory, read-only memory, flash memory), electronicstorage unit 815 (e.g., hard disk), communication interface 820 (e.g.,network adapter) for communicating with one or more other systems, andperipheral devices 825, such as cache, other memory, data storage and/orelectronic display adapters. The memory 810, storage unit 815, interface820 and peripheral devices 825 are in communication with the CPU 805through a communication bus (solid lines), such as a motherboard. Thestorage unit 815 can be a data storage unit (or data repository) forstoring data. The digital processing device 801 can be operativelycoupled to a computer network (“network”) 830 with the aid of thecommunication interface 820. The network 830 can be the Internet, aninternet and/or extranet, or an intranet and/or extranet that is incommunication with the Internet. The network 830 in some cases is atelecommunication and/or data network. The network 830 can include oneor more computer servers, which can enable distributed computing, suchas cloud computing. The network 830, in some cases with the aid of thedevice 801, can implement a peer-to-peer network, which may enabledevices coupled to the device 801 to behave as a client or a server.

Continuing to refer to FIG. 8, the CPU 805 can execute a sequence ofmachine-readable instructions, which can be embodied in a program orsoftware. The instructions may be stored in a memory location, such asthe memory 810. The instructions can be directed to the CPU 805, whichcan subsequently program or otherwise configure the CPU 805 to implementmethods of the present disclosure. Examples of operations performed bythe CPU 805 can include fetch, decode, execute, and write back. The CPU805 can be part of a circuit, such as an integrated circuit. One or moreother components of the device 801 can be included in the circuit. Insome cases, the circuit is an application specific integrated circuit(ASIC) or a field programmable gate array (FPGA).

Continuing to refer to FIG. 8, the storage unit 815 can store files,such as drivers, libraries and saved programs. The storage unit 815 canstore user data, e.g., user preferences and user programs. The digitalprocessing device 801 in some cases can include one or more additionaldata storage units that are external, such as located on a remote serverthat is in communication through an intranet or the Internet.

Continuing to refer to FIG. 8, the digital processing device 801 cancommunicate with one or more remote computer systems through the network830. For instance, the device 801 can communicate with a remote computersystem of a user. Examples of remote computer systems include personalcomputers (e.g., portable PC), slate or tablet PCs (e.g., Apple® iPad,Samsung® Galaxy Tab), telephones, Smart phones (e.g., Apple® iPhone,Android-enabled device, Blackberry®), or personal digital assistants.

Methods as described herein can be implemented by way of machine (e.g.,computer processor) executable code stored on an electronic storagelocation of the digital processing device 801, such as, for example, onthe memory 810 or electronic storage unit 815. The machine executable ormachine readable code can be provided in the form of software. Duringuse, the code can be executed by the processor 805. In some cases, thecode can be retrieved from the storage unit 815 and stored on the memory810 for ready access by the processor 805. In some situations, theelectronic storage unit 815 can be precluded, and machine-executableinstructions are stored on memory 810.

Non-Transitory Computer Readable Storage Medium

In some embodiments, the platforms, systems, media, and methodsdisclosed herein include one or more non-transitory computer readablestorage media encoded with a program including instructions executableby the operating system of an optionally networked digital processingdevice. In further embodiments, a computer readable storage medium is atangible component of a digital processing device. In still furtherembodiments, a computer readable storage medium is optionally removablefrom a digital processing device. In some embodiments, a computerreadable storage medium includes, by way of non-limiting examples,CD-ROMs, DVDs, flash memory devices, solid state memory, magnetic diskdrives, magnetic tape drives, optical disk drives, cloud computingsystems and services, and the like. In some cases, the program andinstructions are permanently, substantially permanently,semi-permanently, or non-transitorily encoded on the media.

Computer Program

In some embodiments, the platforms, systems, media, and methodsdisclosed herein include at least one computer program, or use of thesame. A computer program includes a sequence of instructions, executablein the digital processing device's CPU, written to perform a specifiedtask. Computer readable instructions may be implemented as programmodules, such as functions, objects, Application Programming Interfaces(APIs), data structures, and the like, that perform particular tasks orimplement particular abstract data types. In light of the disclosureprovided herein, those of skill in the art will recognize that acomputer program may be written in various versions of variouslanguages.

The functionality of the computer readable instructions may be combinedor distributed as desired in various environments. In some embodiments,a computer program comprises one sequence of instructions. In someembodiments, a computer program comprises a plurality of sequences ofinstructions. In some embodiments, a computer program is provided fromone location. In other embodiments, a computer program is provided froma plurality of locations. In various embodiments, a computer programincludes one or more software modules. In various embodiments, acomputer program includes, in part or in whole, one or more webapplications, one or more mobile applications, one or more standaloneapplications, one or more web browser plug-ins, extensions, add-ins, oradd-ons, or combinations thereof.

Web Application

In some embodiments, a computer program includes a web application. Inlight of the disclosure provided herein, those of skill in the art willrecognize that a web application, in various embodiments, utilizes oneor more software frameworks and one or more database systems. In someembodiments, a web application is created upon a software framework suchas Microsoft® .NET or Ruby on Rails (RoR). In some embodiments, a webapplication utilizes one or more database systems including, by way ofnon-limiting examples, relational, non-relational, object oriented,associative, and XML database systems. In further embodiments, suitablerelational database systems include, by way of non-limiting examples,Microsoft® SQL Server, mySQL™, and Oracle®. Those of skill in the artwill also recognize that a web application, in various embodiments, iswritten in one or more versions of one or more languages. A webapplication may be written in one or more markup languages, presentationdefinition languages, client-side scripting languages, server-sidecoding languages, database query languages, or combinations thereof. Insome embodiments, a web application is written to some extent in amarkup language such as Hypertext Markup Language (HTML), ExtensibleHypertext Markup Language (XHTML), or eXtensible Markup Language (XML).In some embodiments, a web application is written to some extent in apresentation definition language such as Cascading Style Sheets (CSS).In some embodiments, a web application is written to some extent in aclient-side scripting language such as Asynchronous JavaScript and XML(AJAX), Flash® ActionScript, JavaScript, or Silverlight®. In someembodiments, a web application is written to some extent in aserver-side coding language such as Active Server Pages (ASP),ColdFusion®, Perl, Java™, JavaServer Pages (JSP), Hypertext Preprocessor(PHP), Python™, Ruby, Tcl, Smalltalk, WebDNA®, or Groovy. In someembodiments, a web application is written to some extent in a databasequery language such as Structured Query Language (SQL). In someembodiments, a web application integrates enterprise server productssuch as IBM® Lotus Domino®. In some embodiments, a web applicationincludes a media player element. In various further embodiments, a mediaplayer element utilizes one or more of many suitable multimediatechnologies including, by way of non-limiting examples, Adobe® Flash®,HTML 5, Apple® QuickTime®, Microsoft® Silverlight®, Java™, and Unity®.

Referring to FIG. 9, in a particular embodiment, an applicationprovision system comprises one or more databases 900 accessed by arelational database management system (RDBMS) 910. Suitable RDBMSsinclude Firebird, MySQL, PostgreSQL, SQLite, Oracle Database, MicrosoftSQL Server, IBM DB2, IBM Informix, SAP Sybase, SAP Sybase, Teradata, andthe like. In this embodiment, the application provision system furthercomprises one or more application severs 920 (such as Java servers, .NETservers, PHP servers, and the like) and one or more web servers 930(such as Apache, IIS, GWS and the like). The web server(s) optionallyexpose one or more web services via app application programminginterfaces (APIs) 940. Via a network, such as the Internet, the systemprovides browser-based and/or mobile native user interfaces.

Referring to FIG. 10, in a particular embodiment, an applicationprovision system alternatively has a distributed, cloud-basedarchitecture 1000 and comprises elastically load balanced, auto-scalingweb server resources 1010 and application server resources 1020 as wellsynchronously replicated databases 1030.

Mobile Application

In some embodiments, a computer program includes a mobile applicationprovided to a mobile digital processing device. In some embodiments, themobile application is provided to a mobile digital processing device atthe time it is manufactured. In other embodiments, the mobileapplication is provided to a mobile digital processing device via thecomputer network described herein.

In view of the disclosure provided herein, a mobile application iscreated by techniques known to those of skill in the art using hardware,languages, and development environments known to the art. Those of skillin the art will recognize that mobile applications are written inseveral languages. Suitable programming languages include, by way ofnon-limiting examples, C, C++, C #, Objective-C, Java™, Javascript,Pascal, Object Pascal, Python™, Ruby, VB.NET, WML, and XHTML/HTML withor without CSS, or combinations thereof.

Suitable mobile application development environments are available fromseveral sources. Commercially available development environmentsinclude, by way of non-limiting examples, AirplaySDK, alcheMo,Appcelerator Celsius, Bedrock, Flash Lite, .NET Compact Framework,Rhomobile, and WorkLight Mobile Platform. Other development environmentsare available without cost including, by way of non-limiting examples,Lazarus, MobiFlex, MoSync, and Phonegap. Also, mobile devicemanufacturers distribute software developer kits including, by way ofnon-limiting examples, iPhone and iPad (iOS) SDK, Android™ SDK,BlackBerry® SDK, BREW SDK, Palm® OS SDK, Symbian SDK, webOS SDK, andWindows® Mobile SDK.

Those of skill in the art will recognize that several commercial forumsare available for distribution of mobile applications including, by wayof non-limiting examples, Apple® App Store, Google® Play, Chrome WebStore, BlackBerry® App World, App Store for Palm devices, App Catalogfor webOS, Windows® Marketplace for Mobile, Ovi Store for Nokia®devices, Samsung® Apps, and Nintendo® DSi Shop.

Software Modules

In some embodiments, the platforms, systems, media, and methodsdisclosed herein include software, server, and/or database modules, oruse of the same. In view of the disclosure provided herein, softwaremodules are created by techniques known to those of skill in the artusing machines, software, and languages known to the art. The softwaremodules disclosed herein are implemented in a multitude of ways. Invarious embodiments, a software module comprises a file, a section ofcode, a programming object, a programming structure, or combinationsthereof. In further various embodiments, a software module comprises aplurality of files, a plurality of sections of code, a plurality ofprogramming objects, a plurality of programming structures, orcombinations thereof. In various embodiments, the one or more softwaremodules comprise, by way of non-limiting examples, a web application, amobile application, and a standalone application. In some embodiments,software modules are in one computer program or application. In otherembodiments, software modules are in more than one computer program orapplication. In some embodiments, software modules are hosted on onemachine. In other embodiments, software modules are hosted on more thanone machine. In further embodiments, software modules are hosted oncloud computing platforms. In some embodiments, software modules arehosted on one or more machines in one location. In other embodiments,software modules are hosted on one or more machines in more than onelocation.

Databases

In some embodiments, the platforms, systems, media, and methodsdisclosed herein include one or more databases, or use of the same. Inview of the disclosure provided herein, those of skill in the art willrecognize that many databases are suitable for storage and retrieval ofspatial characteristics of a 3D object. In various embodiments, suitabledatabases include, by way of non-limiting examples, relationaldatabases, non-relational databases, object oriented databases, objectdatabases, entity-relationship model databases, associative databases,and XML databases. Further non-limiting examples include SQL,PostgreSQL, MySQL, Oracle, DB2, and Sybase. In some embodiments, adatabase is internet-based. In further embodiments, a database isweb-based. In still further embodiments, a database is cloudcomputing-based. In other embodiments, a database is based on one ormore local computer storage devices.

EXAMPLES

The following illustrative examples are representative of embodiments ofthe software applications, systems, and methods described herein and arenot meant to be limiting in any way.

Example 1—Authentication of a User

A user attempts to access a banking application on their mobile device.To grant access to the banking account of the user, the applicationprompts the user to position their mobile device such that the screen ofthe mobile device points towards their face.

The application then captures a first image data of the user, via thefront-facing camera, while simultaneously displaying a first anauthentication pattern image on the screen of the mobile devicecomprising a high brightness region and a low brightness region, thatare arranged in two vertical bands. The application then captures asecond image data of the user, via the front-facing camera, whilesimultaneously displaying a second authentication pattern image on thescreen of the mobile device comprising a high brightness region and alow brightness region that are arranged in two horizontal bands. Theapplication then captures a third image data of the user, via thefront-facing camera, while simultaneously displaying a thirdauthentication pattern image on the screen of the mobile devicecomprising two high brightness regions and two low brightness regionsthat are arranged in four alternating vertical bands. The applicationthen captures a fourth image data of the user, via the front-facingcamera, while simultaneously displaying a fourth authentication patternimage on the screen of the mobile device comprising two high brightnessregions and two low brightness regions that are arranged in fouralternating horizontal bands. The application then captures a fifthimage data of the user, via the front-facing camera, whilesimultaneously displaying a fifth authentication pattern image on thescreen of the mobile device comprising a plurality of high brightnessregions and a plurality of low brightness regions that are arranged inalternating horizontal bands. The application then captures a sixthimage data of the user, via the front-facing camera, whilesimultaneously displaying a sixth authentication pattern image on thescreen of the mobile device comprising a plurality of high brightnessregions and a plurality of low brightness regions that are arranged inalternating vertical bands. The application then captures a seventhimage data of the user, via the front-facing camera, whilesimultaneously displaying a seventh authentication pattern image on thescreen of the mobile device comprising two horizontal bands of highbrightness regions across the top and bottom of the screen, and a singlehorizontal band of a low brightness region across the middle of thescreen. The application then captures an eighth image data of the user,via the front-facing camera, while simultaneously displaying an eighthauthentication pattern image on the screen of the mobile devicecomprising vertical bands of high brightness regions along the left andright sides of the screen, and a single vertical band of a lowbrightness region along the middle of the screen. The application thencaptures a ninth image data of the user, via the front-facing camera,while simultaneously displaying a ninth authentication pattern image onthe screen of the mobile device comprising a plurality of randomlyshaped and positioned, high brightness regions and low brightnessregions. The application then further captures additional image data ofthe user, via the front-facing camera, while simultaneously displaying avideo authentication pattern on the screen of the mobile devicecomprising a circular high brightness region moving clockwise in anelliptical pattern, with a background comprising a low brightnessregion.

Once the mobile device determines a current spatial characteristic ofthe user from the image data and the authentication patterns, the mobiledevice grants the user access to the banking account if no spoofing isdetected, or blocks access to the banking account if spoofing isdetected. The mobile device may transmit information related to thetime, location, device, account, or any combination thereof, associatedwith the spoofing attempt, to an appropriate notification channel and/ordatabase for further processing.

Example 2—Encoded Authentication Pattern

A user attempts to access a stock trading application on their mobiledevice. To grant access to the stock trading account of the user, theapplication prompts the user to position their mobile device such thatthe screen of the mobile device points towards their face. Theapplication then captures image data of the user, via the front-facingcamera, while simultaneously displaying a authentication pattern on thescreen of the mobile device, wherein the authentication patterncomprises a plurality of images, wherein each image comprises aplurality of regions, wherein at least one of the regions varies in atleast one of: brightness, position, size, shape, and color over timecausing a variance of lighting effects which create highlights andshadows on the user over time, and wherein one image in theauthentication pattern comprises an encoding image.

The encoding image comprises a region of bright red pixels on the lefthalf of the screen of the mobile device, and a region of bright greenpixels on the right half of the screen of the mobile device, which isunique to the user, the user's account, the time of the authenticationattempt, the day of the authentication attempt, and the location of theuser during the authentication attempt. The mobile device grants theuser access to the stock trading account if red and green highlights andshadows on the user, captured by the 2D representation, correlate withthe encoding image, or blocks access to the stock trading account if the2D representation does not display red and green highlights and shadowson the user correlating with the encoding image. The mobile device thenalerts an authority with information related to the time, location,device, account, or any combination thereof, associated with theattempted access.

What is claimed is:
 1. A mobile device comprising: a front-facingcamera, a front-facing screen, at least one processor, a memory, and acomputer program including instructions executable by the at least oneprocessor to run an application for recognizing a class or within-classidentity of a 3D object in a mobile object detection and identityrecognition process, the application comprising: a) a software moduleinstructing a user to orient the front-facing camera of the mobiledevice in a fixed position and orientation relative to the object; b) asoftware module capturing, via the front-facing camera: i) a first imagedata of the 3D object while the mobile device is in the fixed positionand orientation relative to the object, and while displaying, via thefront-facing screen, a first identification pattern, the firstidentification pattern comprising a plurality of first identificationpattern regions, wherein at least one of the first identificationpattern regions varies from another first identification pattern region,the first identification pattern causing a first variance of lightingeffects on the 3D object, which creates a first set of highlights andshadows on the 3D object, wherein the first image data comprises thefirst set of highlights and shadows, and ii) a second image data of the3D object while the mobile device is in the fixed position andorientation relative to the object, and while displaying, via thefront-facing screen, a second identification pattern after displayingthe first identification pattern, wherein the second identificationpattern is different from the first identification pattern, the secondidentification pattern comprising a plurality of second identificationpattern regions, wherein at least one of the second identificationpattern regions varies from another second identification patternregions, the second identification pattern causing a second variance oflighting effects on the 3D object, which creates a second set ofhighlights and shadows on the 3D object, wherein the second image datacomprises the second set of highlights and shadows; c) a software modulecalculating a difference between the first image data and the secondimage data to determine a current spatial characteristic of the 3Dobject; and d) a software module determining the class, or thewithin-class identity of the 3D object, in the mobile detection andidentity recognition process by comparing the current spatialcharacteristic of the 3D object with a stored reference spatialcharacteristic of the 3D object.
 2. The device of claim 1, wherein the3D object comprises a face, a palm (palm print), a finger (fingerprint),or an ear.
 3. The device of claim 1, wherein the mobile object detectionand identity recognition process is performed solely or in combinationwith other processes of object detection and identity recognition. 4.The device of claim 1, wherein at least one of the first image data andthe second image data comprises a plurality of photographs of the 3Dobject, a video of the 3D object, or both.
 5. The device of claim 1,wherein at least one of the first identification pattern and the secondidentification pattern comprises a plurality of images, a video, orboth.
 6. The device of claim 1, wherein the at least one of theplurality of the first identification pattern regions and the pluralityof the second identification pattern regions are arranged in two or morevertical or horizontal bands.
 7. The device of claim 1, wherein thevariation within at least one of the first identification patternregions and the second identification pattern regions forms a regularpulse or a random pulse in the first or second identification pattern.8. The device of claim 1, wherein the variation within at least one ofthe first identification pattern regions and the second identificationpattern regions forms a translation or rotation of the firstidentification pattern region or the second identification patternregion in the first identification pattern or the second identificationpattern, forms a contraction or expansion of the first identificationpattern region or the second identification pattern region in the firstidentification pattern or the second identification pattern, or both. 9.The device of claim 1, wherein the variation within at least one of thefirst identification pattern regions and the second identificationpattern regions encodes information in the first or secondidentification pattern.
 10. A system for recognizing a class orwithin-class identity of a 3D object, in a mobile object detection andidentity recognition process, the system comprising: a mobile devicecomprising a front-facing camera, a front-facing screen, at least oneprocessor, a memory; and a server comprising at least one processor anda memory: the mobile device configured to: a) instruct a user to orientthe front-facing camera of the mobile device in a fixed position andorientation relative to the object; b) capture, via the front-facingcamera, i) a first image data of the 3D object while the mobile deviceis in the fixed position and orientation relative to the object, andwhile displaying, via the front-facing screen, a first identificationpattern, the first identification pattern comprising a plurality offirst identification pattern regions, wherein at least one of the firstidentification pattern regions varies from another first identificationpattern region, the first identification pattern causing a firstvariance of lighting effects on the 3D object, which creates a first setof highlights and shadows on the 3D object, wherein the first image datacomprises the first set of highlights and shadows, and ii) a secondimage data of the 3D object while the mobile device is in the fixedposition and orientation relative to the object, and while displaying,via the front-facing screen, a second identification pattern afterdisplaying the first identification pattern, wherein the secondidentification pattern is different from the first identificationpattern, the second identification pattern comprising a plurality ofsecond identification pattern regions, wherein at least one of thesecond identification pattern regions varies from another secondidentification pattern regions, the second identification patterncausing a second variance of lighting effects on the 3D object, whichcreates a second set of highlights and shadows on the 3D object, whereinthe second image data comprises the second set of highlights andshadows; transmit the first image data and the second image data to theserver; the server configured to: a) receive the first image data andthe second image data from the mobile device; b) calculate a differencebetween the first image data and the second image data to determine acurrent spatial characteristic of the 3D object; c) determine the class,or the within-class identity of the 3D object in the mobile objectdetection and identity recognition process by comparing the currentspatial characteristic of the 3D object with a stored reference spatialcharacteristic of the 3D object; and d) transmit the class, or thewithin-class identity to the mobile device.
 11. The system of claim 10,wherein the 3D object comprises a face, a palm (palm print), a finger(fingerprint), or an ear.
 12. The system of claim 10, wherein the mobileobject detection and identity recognition process is performed solely orin combination with other processes of object detection and identityrecognition.
 13. The system of claim 10, wherein at least one of thefirst image data and the second image data comprises a plurality ofphotographs of the 3D object, a video of the 3D object, or both.
 14. Thesystem of claim 10, wherein at least one of the first identificationpattern and the second identification pattern comprises a plurality ofimages, a video, or both.
 15. The system of claim 10, wherein at leastone of the plurality of first identification pattern regions and secondidentification pattern regions are arranged in two or more vertical orhorizontal bands.
 16. The system of claim 10, wherein the variationwithin at least one of the first identification pattern regions and thesecond identification pattern regions forms a regular pulse or a randompulse in the first or second identification pattern.
 17. The system ofclaim 10, wherein the variation within at least one of the firstidentification pattern regions and the second identification patternregions forms a translation or rotation of the first identificationpattern region or the second identification pattern region in the firstidentification pattern or the second identification pattern, forms acontraction or expansion of the first identification pattern region orthe second identification pattern region in the first identificationpattern or the second identification pattern, or both.
 18. The system ofclaim 10, wherein the variation within at least one of the firstidentification pattern regions and the second identification patternregions encodes information in the first or second identificationpattern.
 19. A method of recognizing a class or within-class identity ofa 3D object, in a mobile object detection and identity recognitionprocess, the method comprising: a) instructing a user to orient afront-facing camera of a mobile device in a fixed position andorientation relative to the 3D object; b) capturing, via a front-facingcamera of a mobile device, i) a first image data of the 3D object whilethe mobile device is in the fixed position and orientation relative tothe object, and while displaying, via the front-facing screen, a firstidentification pattern, the first identification pattern comprising aplurality of first identification pattern regions, wherein at least oneof the first identification pattern regions varies from another firstidentification pattern region, the first identification pattern causinga first variance of lighting effects on the 3D object, which creates afirst set of highlights and shadows on the 3D object, wherein the firstimage data comprises the first set of highlights and shadows, and ii) asecond image data of the 3D object while the mobile device is in thefixed position and orientation relative to the object, and whiledisplaying, via the front-facing screen, a second identification patternafter displaying the first identification pattern, wherein the secondidentification pattern is different from the first identificationpattern, the second identification pattern comprising a plurality ofsecond identification pattern regions, wherein at least one of thesecond identification pattern regions varies from another secondidentification pattern regions, the second identification patterncausing a second variance of lighting effects on the 3D object, whichcreates a second set of highlights and shadows on the 3D object, whereinthe second image data comprises the second set of highlights andshadows; c) calculating a difference between the first image data andthe second image data to determine a current spatial characteristic ofthe 3D object; and d) determining the class, or the within-classidentity of the 3D in the mobile object detection and identityrecognition process by comparing the current spatial characteristic ofthe 3D object with a stored reference spatial characteristic of the 3Dobject.